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Noelle Brown; Sara Nurollahian; Eliane S. Wiese – ACM Transactions on Computing Education, 2025
While there have been many calls for teaching ethics and responsible computing, it is unclear how responsible computing instruction and technical learning interact. Some instructors even hesitate to include ethics in their courses, fearing it might distract students from learning technical computing content. An approach called…
Descriptors: Teaching Methods, Computer Science Education, Intervention, Ethics
Paraskevi Topali; Ruth Cobos; Unai Agirre-Uribarren; Alejandra Martínez-Monés; Sara Villagrá-Sobrino – Journal of Computer Assisted Learning, 2024
Background: Personalised and timely feedback in massive open online courses (MOOCs) is hindered due to the large scale and diverse needs of learners. Learning analytics (LA) can support scalable interventions, however they often lack pedagogical and contextual grounding. Previous research claimed that a human-centred approach in the design of LA…
Descriptors: Learning Analytics, MOOCs, Feedback (Response), Intervention
Reem El Sherif; Pierre Pluye; Quan Nha Hong; Benoît Rihoux – Research Synthesis Methods, 2024
Qualitative comparative analysis (QCA) is a hybrid method designed to bridge the gap between qualitative and quantitative research in a case-sensitive approach that considers each case holistically as a complex configuration of conditions and outcomes. QCA allows for multiple conjunctural causation, implying that it is often a combination of…
Descriptors: Comparative Analysis, Qualitative Research, Statistical Analysis, Researchers
Tan, Teck Kiang – Practical Assessment, Research & Evaluation, 2022
Power analysis based on the analytical t-test is an important aspect of a research study to determine the sample size required to detect the effect for the comparison of two means. The current paper presents a reader-friendly procedure for carrying out the t-test power analysis using the various R add-on packages. While there is a growing of R…
Descriptors: Programming Languages, Sample Size, Bayesian Statistics, Intervention
Mümüne Merve Parlak; Aysen Köse; Murat Güç; Özlem Bizpinar Munis – International Journal of Language & Communication Disorders, 2024
Background: Alzheimer's disease (AD) is a progressive neurodegenerative disease. Cognitive functions and communication skills worsen as the disease progresses, thereby reducing patients' independence levels. Therefore, recommending software that can be used at home may be a useful means of slowing down the cognitive and communicative decline in…
Descriptors: Handheld Devices, Alzheimers Disease, Cognitive Ability, Communication (Thought Transfer)
Tom Neuschafer – Journal of Educators Online, 2025
Online instructors have identified several issues that must be addressed to facilitate better online learning experiences, including authentic experiential education, building community, technology for remote learning, and supporting learners. Online forums are often used by users to express their frustrations, feelings, jokes, and even…
Descriptors: Computer Mediated Communication, Second Language Learning, Handheld Devices, Educational Technology
Russell, Amy; Smyth, Sinéad – Journal of Research in Special Educational Needs, 2023
The field of special education is thought to be a stressful profession due to the complex needs of the students. The current study aimed to assess the effectiveness of a mindfulness-based smartphone application intervention for reducing burnout in special educators. We used the Copenhagen Burnout Inventory scale (with three subscales; personal,…
Descriptors: Special Education Teachers, Teacher Burnout, Metacognition, Intervention
McLoughlin, Shane; Tyndall, Ian; Pereira, Antonina – Journal of Behavioral Education, 2022
In recent years, small-scale studies have suggested that we may be able to substantially strengthen children's general cognitive abilities and intelligence quotient (IQ) scores using a relational operant skills training program (SMART). Only one of these studies to date has included an active Control Condition, and that study reported the smallest…
Descriptors: Cognitive Ability, Intelligence Quotient, Early Adolescents, Programming
Gary Robinaugh; Maya L. Henry; Robert Cavanaugh; Stephanie M. Grasso – Journal of Speech, Language, and Hearing Research, 2024
Purpose: The purpose of this study was to investigate the effectiveness of a self-administered naming treatment for one individual, B.N., presenting with semantic variant primary progressive aphasia (svPPA) and a history of traumatic brain injury (TBI). Method: Naming treatment included components of Lexical Retrieval Cascade Treatment and was…
Descriptors: Aphasia, Head Injuries, Brain, Naming
Austin T. Wyman; Zhiyong Zhang – Grantee Submission, 2023
Emotion recognition application programming interface (API) is a recent advancement in computing technology that synthesizes computer vision, machine-learning algorithms, deep-learning neural networks, and other information to detect and label human emotions. The strongest iterations of this technology are produced by technology giants with large,…
Descriptors: Emotional Response, Computer Software, Emotional Problems, Autism Spectrum Disorders
Dragos-Georgian Corlatescu; Micah Watanabe; Stefan Ruseti; Mihai Dascalu; Danielle S. McNamara – Grantee Submission, 2024
Modeling reading comprehension processes is a critical task for Learning Analytics, as accurate models of the reading process can be used to match students to texts, identify appropriate interventions, and predict learning outcomes. This paper introduces an improved version of the Automated Model of Comprehension, namely version 4.0. AMoC has its…
Descriptors: Computer Software, Artificial Intelligence, Learning Analytics, Natural Language Processing
Frank Niklas; Efsun Birtwistle; Anna Mues; Astrid Wirth – Child Development, 2025
The usage of high-quality learning applications (apps) at home may increase children's mathematical and literacy competencies. This approach was tested in a family intervention study. Intervention families (n = 302) in two German cohorts (N = 500; M (SD)[subscript age] = 61.0 (4.6) months; n[female gender symbol] = 302) received tablets with newly…
Descriptors: Foreign Countries, Educational Technology, Technology Uses in Education, Tablet Computers
Pearson, Heather Ann; Montazami, Armaghan; Dubé, Adam Kenneth – British Journal of Educational Technology, 2023
Researchers recommend that parents look for five benchmarks as indicators of quality educational apps (ie, scaffolding, curriculum, development team, feedback, learning theory), yet results show that parents undervalue some of these benchmarks. The current study examined if a short video-based intervention would enhance parents' value-judgements…
Descriptors: Computer Software, Benchmarking, Video Technology, Intervention
Bülbül, Buket Özüm; Güler, Mustafa – E-Learning and Digital Media, 2023
Geometric habits of mind (GHoM) are the approaches that individuals use to solve geometry problems. This study aimed to determine the effect of dynamic geometry software (DGS) in activating the GHoM of pre-service mathematics teachers. The study was conducted with six teacher candidates who were enrolled in a semester-long course titled…
Descriptors: Cognitive Processes, Problem Solving, Geometry, Computer Software
Tola Bekene Bedada; M. F. Machaba – Education Inquiry, 2024
This article presents an instructional technology-based cycle model intended to support and facilitate the teaching and learning of mathematics, particularly calculus. The study used quantitative methods with quasi-experimental research that uses non-randomised assignments of the study group that are categorised into experimental and control…
Descriptors: Models, Mathematics Instruction, Computer Software, Educational Technology